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   "source": [
    "import onnxruntime\n",
    "import numpy as np\n",
    "from PIL import Image\n",
    "\n",
    "\n",
    "# 加载ONNX模型  2分\n",
    "ort_session = __________________\n",
    "\n",
    "\n",
    "# 加载图像 2分\n",
    "image = __________________('L')  # 转为灰度图\n",
    "\n",
    "\n",
    "#图像预处理 \n",
    "image = __________________((28, 28))  # 调整大小为MNIST模型的输入尺寸2分\n",
    "image_array = __________________(__________________, dtype=np.float32)  # 转为numpy数组2分\n",
    "image_array = __________________(__________________, axis=0)  # 添加batch维度2分\n",
    "image_array = __________________(__________________, axis=0)  # 添加通道维度2分\n",
    "\n",
    "\n",
    "#返回模型输入列表 2分\n",
    "ort_inputs = {__________________()[0].name: image_array}\n",
    "# 执行预测 2分\n",
    "ort_outs = __________________(None, ort_inputs)\n",
    "\n",
    "\n",
    "# 获取预测结果 2分\n",
    "predicted_class = __________________\n",
    "\n",
    "\n",
    "# 输出预测结果\n",
    "print(f\"Predicted class: {predicted_class}\")\n"
   ]
  }
 ],
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